U.S. patent application number 17/480243 was filed with the patent office on 2022-03-31 for method and apparatus for image noise reduction.
This patent application is currently assigned to Siemens Healthcare GmbH. The applicant listed for this patent is Siemens Healthcare GmbH. Invention is credited to Magdalena HERBST, Steffen KAPPLER, Ludwig RITSCHL.
Application Number | 20220096034 17/480243 |
Document ID | / |
Family ID | |
Filed Date | 2022-03-31 |
United States Patent
Application |
20220096034 |
Kind Code |
A1 |
HERBST; Magdalena ; et
al. |
March 31, 2022 |
METHOD AND APPARATUS FOR IMAGE NOISE REDUCTION
Abstract
A method and a system are for image noise reduction. In an
embodiment, the method includes producing a recorded image;
establishing an amount of noise of the recorded image; decomposing
the amount of noise into a number of N frequency-dependent noise
components for N frequency bands, the number of N
frequency-dependent noise components including respective data
points respectively reproducing noise, of the amount of noise in
the recorded image, for the respective frequency bands of the N
frequency bands; examining the number of N frequency-dependent
noise components for outlier data points, where an intensity lies
outside a range of values, and forming moderated noise components
by moderation of values of the outlier data points established in
the examining of the number of N frequency-dependent noise
components; and subtracting the moderated noise components from the
recorded image.
Inventors: |
HERBST; Magdalena;
(Erlangen, DE) ; KAPPLER; Steffen; (Effeltrich,
DE) ; RITSCHL; Ludwig; (Buttenheim, DE) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Siemens Healthcare GmbH |
Erlangen |
|
DE |
|
|
Assignee: |
Siemens Healthcare GmbH
Erlangen
DE
|
Appl. No.: |
17/480243 |
Filed: |
September 21, 2021 |
International
Class: |
A61B 6/00 20060101
A61B006/00; A61B 6/03 20060101 A61B006/03; A61B 6/02 20060101
A61B006/02 |
Foreign Application Data
Date |
Code |
Application Number |
Sep 25, 2020 |
DE |
10 2020 212 089.7 |
Claims
1. A method for image noise reduction, comprising: producing a
recorded image; establishing an amount of noise of the recorded
image; decomposing the amount of noise into a number of N
frequency-dependent noise components for N frequency bands, the
number of N frequency-dependent noise components including
respective data points respectively reproducing noise, of the
amount of noise in the recorded image, for the respective frequency
bands of the N frequency bands; examining the number of N
frequency-dependent noise components for outlier data points, where
an intensity lies outside a range of values, and forming moderated
noise components by moderation of values of the outlier data points
established in the examining of the number of N frequency-dependent
noise components; and subtracting the moderated noise components
from the recorded image.
2. The method of claim 1, wherein the recorded image has been
produced via x-rays.
3. The method of claim 1, wherein the amount of noise of the
recorded image is established, in the establishing, via a image
noise reduction algorithm.
4. The method of claim 1, wherein the decomposing of the amount of
noise is carried out based upon a Laplace pyramid, a Fast-Fourier
transformation or a wavelet transformation.
5. The method of claim 1, wherein the respective data points of the
number of N frequency-dependent noise components are image points
of an image or reconstructable to image points of an image,
representing the respective noise component for the respective
frequency band.
6. The method of claim 1, wherein the examining of the number of N
frequency-dependent noise components for outlier data points and
the forming of the moderated noise components is carried out by a
moderation function, to moderate values of the outlier data points
lying outside the range of values and leaving values of the outlier
data points within the range of values unchanged.
7. The method of claim 1, wherein before the subtracting of the
moderated noise components from the recorded image, combining the
moderated noise components with the outlier data points dealt with
to form one moderated amount of noise, and wherein the N frequency
bands of the noise components, taken together, produce a contiguous
frequency range.
8. The method of claim 1, wherein as part of the image recording, a
noise behavior of equipment used for recording is at least one of
measured and calibrated, and wherein at least one of the moderation
function depends on the noise behavior measured and the image
recording takes place after the calibrating.
9. The method of claim 1, wherein the amount of noise is decomposed
during the decomposing into more than two noise components.
10. An apparatus for image noise reduction, comprising: at least
one of an imaging system designed to produce a recorded image and a
data interface to receive a recorded image; a noise reduction unit
to establish an amount of noise of the recorded image; a
decomposition unit to decompose the amount of noise into a number
of N frequency-dependent noise components for N frequency bands,
the number of N frequency-dependent noise components including
respective data points respectively reproducing noise, of the
amount of noise in the recorded image, at respective points of the
recorded image for respective frequency bands of the N frequency
bands; a moderation unit to examine the number of N
frequency-dependent noise components for outlier data points, where
an intensity lies outside a range of values, and to form moderated
noise components by moderation of values of the outlier data points
established in the examining of the number of N frequency-dependent
noise; and a subtraction unit to subtract the moderated noise
components from the recorded image.
11. The apparatus of claim 10, further comprising: a combination
unit, to combine the moderated noise components into one moderated
amount of noise before the moderated noise components are
subtracted by the subtraction unit from the recorded image (B).
12. A control facility for controlling an imaging system,
comprising: the apparatus of claim 10.
13. An imaging system, comprising the control facility of claim
12.
14. A non-transitory computer program product storing a computer
program, directly loadable into a memory facility of a control
facility, including program sections for carrying out the method of
claim 1 when the computer program is executed in the control
facility.
15. A non-transitory computer-readable medium, storing program
sections readable in and executable by a processor, to carry out
the method of claim 1 when the program sections are executed by the
processor.
16. The method of claim 2, wherein the recorded image has been
produced via x-rays within a framework of a recording method of
radiography, fluoroscopy, mammography, tomography or computed
tomography.
17. The method of claim 2, wherein the recorded image is based on
at least one of a mammography recording and a tomosynthesis
recording.
18. The method of claim 2, wherein the recorded image is a
synthetic 2D-image computed from a tomosynthesis recording or an
image of an intermediate step of a computation.
19. The method of claim 3, wherein image noise reduction algorithm
is based on at least one of BM3D, on an iterative CT image filter
for noise reduction and via artificial intelligence.
20. The method of claim 2, wherein the decomposing of the amount of
noise is carried out based upon a Laplace pyramid, a Fast-Fourier
transformation or a wavelet transformation.
21. The method of claim 2, wherein the respective data points of
the number of N frequency-dependent noise components are image
points of an image or reconstructable to image points of an image,
representing the respective noise component for the respective
frequency band.
22. The method of claim 3, wherein the recorded image is subdivided
into the amount of noise and a component of image information.
23. The method of claim 6, wherein the values of the outlier data
points lying outside the range of values are changed by the
moderation function so that they lie inside the range of values
24. The method of claim 23, the range of values are changed by the
values of the outlier data points being set to limits of the range
of values or, as a distance from the range of values relatively
increases, being adapted to be relatively closer to an average
value of the range of values.
25. The method of claim 9, wherein the amount of noise is
decomposed during the decomposing into three noise components
26. The method of claim 9, wherein noise components with relatively
highest frequency bands are chosen.
27. A control facility for controlling an imaging system,
comprising: the apparatus of claim 11.
28. The imaging system of claim 13, wherein the imaging system is
at least one of a radiography system, a fluoroscopy system, a
mammography system, a tomography system or a computed tomography
system.
Description
PRIORITY STATEMENT
[0001] The present application hereby claims priority under 35
U.S.C. .sctn. 119 to German patent application number
DE102020212089.7 filed Sep. 25, 2020, the entire contents of which
are hereby incorporated herein by reference.
FIELD
[0002] Example embodiments of the invention generally relate to a
method and an apparatus for image noise reduction, in particular of
x-ray images, preferably for statistically motivated,
frequency-based backup of image noise reduction algorithms.
BACKGROUND
[0003] When images are recorded, noise, which can become noticeable
as disturbing to a greater or lesser extent, is always contained in
the images. If these images are to be evaluated, e.g. in an
examination of medical images by a doctor, a large noise component
is very disadvantageous. Therefore the noise in recorded images is
often reduced before an examination by image noise reduction
methods, which are based for example on classical non-linear
filters, iterative methods or specifically on artificial
intelligence AI.
[0004] A known risk that has long existed in the development and
application of image noise reduction algorithms is the
unintentional removal of information relevant to the image, which
can occur as a negative side effect during the reduction of noise
in image data. A further risk is that available structures are
disproportionately processed out or entirely new structures are
even incorrectly inserted. The last point above all relates to
algorithms with AI, since these have been trained with a large but
finite volume of data and thus are not prepared for every
scenario.
[0005] Depending on the method chosen for noise reduction and the
desired level of noise reduction, this risk is low, slight or high.
With medical image data in particular subtle structures can
influence the appraisal, so that it must therefore be insured that
on the one hand these must be preserved, but they must not be
additionally emphasized.
[0006] Conventional noise reduction methods, i.e. methods without
AI, either have parameters with which the algorithm can be set
according to the application, or reduce noise according to a
statistic of the data (e.g. BM3D or an iterative CT image filter
for noise reduction, known as "IRIS" for short). In relation to the
"BM3D" method, the reader is referred to K. Dabov, A. Foi, V.
Katkovnik, and K. Egiazarian "Image denoising by sparse 3d
transformdomain collaborative filtering" (IEEE Transactions on
Image Processing, 16(8):2080-2095, August 2007). In relation to
"IRIS" filters to US 2011/0052030 A1 or DE102009039987A1, the
corresponding German application. With IRIS for example a decision
is made for each image point based on the local statistic as to
whether this involves a noise pixel, which is to be smoothed, or
structure, which is to be preserved.
SUMMARY
[0007] The inventors have discovered that a disadvantage of the
known methods is that the risk portrayed above that structures in
images will be incorrectly deleted, processed out or created.
[0008] At least one embodiment of the present invention specifies
an alternate, more convenient method and/or a corresponding
apparatus for image noise reduction, in particular of x-ray images,
with which at least one of the disadvantages described above will
be reduced or even avoided.
[0009] Embodiments are directed to a method, an apparatus, a
control facility and an imaging system.
[0010] At least one embodiment of the inventive method for image
noise reduction, in particular of x-ray images, comprises:
[0011] production of a recorded image;
[0012] establishing of an amount of noise of the recorded
image;
[0013] decomposition of the amount of noise into a defined number
of N frequency-dependent noise components for N frequency bands,
wherein the noise components comprise data points, which reflect
the noise in the recorded image for the frequency band
concerned;
[0014] examination of the noise components (for a number of their
image points/all image points) for (statistical) outlier image
points of which the intensity lies outside a predetermined range of
values and formation of moderate noise components by moderation of
the values of the outlier image points established in the
examination; and
[0015] subtraction of the moderated noise components from the
recorded image.
[0016] An inventive apparatus for image noise reduction of an
embodiment comprises:
[0017] An (in particular medical) imaging system designed to
produce a recorded image or a data interface for receiving a
recorded image, e.g. a radiography system, mammography system (also
tomosynthesis), fluoroscopy system or a computed tomography
system,
[0018] A noise reduction unit designed to establish an amount of
noise of the recorded image,
[0019] A decomposition unit designed to decompose the amount of
noise into a predetermined number of N frequency-band-dependent
noise components for N frequency bands, wherein the noise
components comprise data points, which reproduce the noise at
points in the recorded image for the frequency band concerned,
[0020] A moderation unit designed to examine the noise components
for outlier data points, the intensity of which lies outside a
predetermined range of values and for formation of moderated noise
components by moderation of the value of the outlier data points
established in the noise components in the examination,
[0021] Optionally a combination unit, which is designed to combine
the moderated noise components into a moderated amount of noise,
(before these are subtracted from the recorded image by the
subsequent subtraction unit), and
[0022] A subtraction unit designed to subtract the moderated noise
components from the recorded image.
[0023] An inventive control facility of an embodiment for control
of an imaging system, in particular a medical imaging system (in
particular for x-ray images), preferably a radiography system,
fluoroscopy system, mammography system or a computed tomography
system, is designed for carrying out an embodiment of an inventive
method and/or comprises an embodiment of an inventive
apparatus.
[0024] An inventive imaging system of an embodiment, in particular
a medical imaging system, preferably a radiography system,
fluoroscopy system, mammography system or a computed tomography
system, comprises an embodiment of an inventive control
facility.
[0025] A method for image noise reduction of an embodiment,
comprises:
[0026] producing a recorded image;
[0027] establishing an amount of noise of the recorded image;
[0028] decomposing the amount of noise into a number of N
frequency-dependent noise components for N frequency bands, the
number of N frequency-dependent noise components including
respective data points respectively reproducing noise, of the
amount of noise in the recorded image, for the respective frequency
bands of the N frequency bands;
[0029] examining the number of N frequency-dependent noise
components for outlier data points, where an intensity lies outside
a range of values, and forming moderated noise components by
moderation of values of the outlier data points established in the
examining of the number of N frequency-dependent noise components;
and
[0030] subtracting the moderated noise components from the recorded
image.
[0031] An apparatus for image noise reduction of an embodiment,
comprises:
[0032] at least one of an imaging system designed to produce a
recorded image and a data interface to receive a recorded
image;
[0033] a noise reduction unit to establish an amount of noise of
the recorded image;
[0034] a decomposition unit to decompose the amount of noise into a
number of N frequency-dependent noise components for N frequency
bands, the number of N frequency-dependent noise components
including respective data points respectively reproducing noise, of
the amount of noise in the recorded image, at respective points of
the recorded image for respective frequency bands of the N
frequency bands;
[0035] a moderation unit to examine the number of N
frequency-dependent noise components for outlier data points, where
an intensity lies outside a range of values, and to form moderated
noise components by moderation of values of the outlier data points
established in the examining of the number of N frequency-dependent
noise; and
[0036] a subtraction unit to subtract the moderated noise
components from the recorded image.
[0037] A control facility for controlling an imaging system of an
embodiment, comprises, the apparatus of an embodiment.
[0038] An imaging system of an embodiment, comprises, the control
facility of an embodiment.
[0039] A non-transitory computer program product of an embodiment
stores a computer program, directly loadable into a memory facility
of a control facility, including program sections for carrying out
the method of an embodiment when the computer program is executed
in the control facility.
[0040] A non-transitory computer-readable medium of an embodiment
stores program sections readable in and executable by a processor,
to carry out the method of an embodiment when the program sections
are executed by the processor.
BRIEF DESCRIPTION OF THE DRAWINGS
[0041] The invention will be explained once again below with
reference to the enclosed figures with the aid of example
embodiments. In this explanation the same components are labeled in
the various figures with the same reference numbers. The figures
are as a rule not true-to-scale. In the figures:
[0042] FIG. 1 shows a rough schematic diagram of a computed
tomography system with an example embodiment of a control facility
with an inventive apparatus for carrying out an example embodiment
of the method.
[0043] FIG. 2 shows the nature of the frequency-dependent noise
components,
[0044] FIG. 3 shows a flowchart for the possible execution sequence
of an example embodiment of an inventive method,
[0045] FIG. 4 shows a preferred moderation function graph,
[0046] FIG. 5 shows a further preferred moderation function
graph,
[0047] FIG. 6 shows a comparison of a result of an example
embodiment of the invention with the prior art,
[0048] FIG. 7 shows noise components of the amount of noise of FIG.
6.
DETAILED DESCRIPTION OF THE EXAMPLE EMBODIMENTS
[0049] The drawings are to be regarded as being schematic
representations and elements illustrated in the drawings are not
necessarily shown to scale. Rather, the various elements are
represented such that their function and general purpose become
apparent to a person skilled in the art. Any connection or coupling
between functional blocks, devices, components, or other physical
or functional units shown in the drawings or described herein may
also be implemented by an indirect connection or coupling. A
coupling between components may also be established over a wireless
connection. Functional blocks may be implemented in hardware,
firmware, software, or a combination thereof.
[0050] Various example embodiments will now be described more fully
with reference to the accompanying drawings in which only some
example embodiments are shown. Specific structural and functional
details disclosed herein are merely representative for purposes of
describing example embodiments. Example embodiments, however, may
be embodied in various different forms, and should not be construed
as being limited to only the illustrated embodiments. Rather, the
illustrated embodiments are provided as examples so that this
disclosure will be thorough and complete, and will fully convey the
concepts of this disclosure to those skilled in the art.
Accordingly, known processes, elements, and techniques, may not be
described with respect to some example embodiments. Unless
otherwise noted, like reference characters denote like elements
throughout the attached drawings and written description, and thus
descriptions will not be repeated. At least one embodiment of the
present invention, however, may be embodied in many alternate forms
and should not be construed as limited to only the example
embodiments set forth herein.
[0051] It will be understood that, although the terms first,
second, etc. may be used herein to describe various elements,
components, regions, layers, and/or sections, these elements,
components, regions, layers, and/or sections, should not be limited
by these terms. These terms are only used to distinguish one
element from another. For example, a first element could be termed
a second element, and, similarly, a second element could be termed
a first element, without departing from the scope of example
embodiments of the present invention. As used herein, the term
"and/or," includes any and all combinations of one or more of the
associated listed items. The phrase "at least one of" has the same
meaning as "and/or".
[0052] Spatially relative terms, such as "beneath," "below,"
"lower," "under," "above," "upper," and the like, may be used
herein for ease of description to describe one element or feature's
relationship to another element(s) or feature(s) as illustrated in
the figures. It will be understood that the spatially relative
terms are intended to encompass different orientations of the
device in use or operation in addition to the orientation depicted
in the figures. For example, if the device in the figures is turned
over, elements described as "below," "beneath," or "under," other
elements or features would then be oriented "above" the other
elements or features. Thus, the example terms "below" and "under"
may encompass both an orientation of above and below. The device
may be otherwise oriented (rotated 90 degrees or at other
orientations) and the spatially relative descriptors used herein
interpreted accordingly. In addition, when an element is referred
to as being "between" two elements, the element may be the only
element between the two elements, or one or more other intervening
elements may be present.
[0053] Spatial and functional relationships between elements (for
example, between modules) are described using various terms,
including "connected," "engaged," "interfaced," and "coupled."
Unless explicitly described as being "direct," when a relationship
between first and second elements is described in the above
disclosure, that relationship encompasses a direct relationship
where no other intervening elements are present between the first
and second elements, and also an indirect relationship where one or
more intervening elements are present (either spatially or
functionally) between the first and second elements. In contrast,
when an element is referred to as being "directly" connected,
engaged, interfaced, or coupled to another element, there are no
intervening elements present. Other words used to describe the
relationship between elements should be interpreted in a like
fashion (e.g., "between," versus "directly between," "adjacent,"
versus "directly adjacent," etc.).
[0054] The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
example embodiments of the invention. As used herein, the singular
forms "a," "an," and "the," are intended to include the plural
forms as well, unless the context clearly indicates otherwise. As
used herein, the terms "and/or" and "at least one of" include any
and all combinations of one or more of the associated listed items.
It will be further understood that the terms "comprises,"
"comprising," "includes," and/or "including," when used herein,
specify the presence of stated features, integers, steps,
operations, elements, and/or components, but do not preclude the
presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof. As
used herein, the term "and/or" includes any and all combinations of
one or more of the associated listed items. Expressions such as "at
least one of," when preceding a list of elements, modify the entire
list of elements and do not modify the individual elements of the
list. Also, the term "example" is intended to refer to an example
or illustration.
[0055] When an element is referred to as being "on," "connected
to," "coupled to," or "adjacent to," another element, the element
may be directly on, connected to, coupled to, or adjacent to, the
other element, or one or more other intervening elements may be
present. In contrast, when an element is referred to as being
"directly on," "directly connected to," "directly coupled to," or
"immediately adjacent to," another element there are no intervening
elements present.
[0056] It should also be noted that in some alternative
implementations, the functions/acts noted may occur out of the
order noted in the figures. For example, two figures shown in
succession may in fact be executed substantially concurrently or
may sometimes be executed in the reverse order, depending upon the
functionality/acts involved.
[0057] Unless otherwise defined, all terms (including technical and
scientific terms) used herein have the same meaning as commonly
understood by one of ordinary skill in the art to which example
embodiments belong. It will be further understood that terms, e.g.,
those defined in commonly used dictionaries, should be interpreted
as having a meaning that is consistent with their meaning in the
context of the relevant art and will not be interpreted in an
idealized or overly formal sense unless expressly so defined
herein.
[0058] Before discussing example embodiments in more detail, it is
noted that some example embodiments may be described with reference
to acts and symbolic representations of operations (e.g., in the
form of flow charts, flow diagrams, data flow diagrams, structure
diagrams, block diagrams, etc.) that may be implemented in
conjunction with units and/or devices discussed in more detail
below. Although discussed in a particularly manner, a function or
operation specified in a specific block may be performed
differently from the flow specified in a flowchart, flow diagram,
etc. For example, functions or operations illustrated as being
performed serially in two consecutive blocks may actually be
performed simultaneously, or in some cases be performed in reverse
order. Although the flowcharts describe the operations as
sequential processes, many of the operations may be performed in
parallel, concurrently or simultaneously. In addition, the order of
operations may be re-arranged. The processes may be terminated when
their operations are completed, but may also have additional steps
not included in the figure. The processes may correspond to
methods, functions, procedures, subroutines, subprograms, etc.
[0059] Specific structural and functional details disclosed herein
are merely representative for purposes of describing example
embodiments of the present invention. This invention may, however,
be embodied in many alternate forms and should not be construed as
limited to only the embodiments set forth herein.
[0060] Units and/or devices according to one or more example
embodiments may be implemented using hardware, software, and/or a
combination thereof. For example, hardware devices may be
implemented using processing circuitry such as, but not limited to,
a processor, Central Processing Unit (CPU), a controller, an
arithmetic logic unit (ALU), a digital signal processor, a
microcomputer, a field programmable gate array (FPGA), a
System-on-Chip (SoC), a programmable logic unit, a microprocessor,
or any other device capable of responding to and executing
instructions in a defined manner. Portions of the example
embodiments and corresponding detailed description may be presented
in terms of software, or algorithms and symbolic representations of
operation on data bits within a computer memory. These descriptions
and representations are the ones by which those of ordinary skill
in the art effectively convey the substance of their work to others
of ordinary skill in the art. An algorithm, as the term is used
here, and as it is used generally, is conceived to be a
self-consistent sequence of steps leading to a desired result. The
steps are those requiring physical manipulations of physical
quantities. Usually, though not necessarily, these quantities take
the form of optical, electrical, or magnetic signals capable of
being stored, transferred, combined, compared, and otherwise
manipulated. It has proven convenient at times, principally for
reasons of common usage, to refer to these signals as bits, values,
elements, symbols, characters, terms, numbers, or the like.
[0061] It should be borne in mind, however, that all of these and
similar terms are to be associated with the appropriate physical
quantities and are merely convenient labels applied to these
quantities. Unless specifically stated otherwise, or as is apparent
from the discussion, terms such as "processing" or "computing" or
"calculating" or "determining" of "displaying" or the like, refer
to the action and processes of a computer system, or similar
electronic computing device/hardware, that manipulates and
transforms data represented as physical, electronic quantities
within the computer system's registers and memories into other data
similarly represented as physical quantities within the computer
system memories or registers or other such information storage,
transmission or display devices.
[0062] In this application, including the definitions below, the
term `module` or the term `controller` may be replaced with the
term `circuit.` The term `module` may refer to, be part of, or
include processor hardware (shared, dedicated, or group) that
executes code and memory hardware (shared, dedicated, or group)
that stores code executed by the processor hardware.
[0063] The module may include one or more interface circuits. In
some examples, the interface circuits may include wired or wireless
interfaces that are connected to a local area network (LAN), the
Internet, a wide area network (WAN), or combinations thereof. The
functionality of any given module of the present disclosure may be
distributed among multiple modules that are connected via interface
circuits. For example, multiple modules may allow load balancing.
In a further example, a server (also known as remote, or cloud)
module may accomplish some functionality on behalf of a client
module.
[0064] Software may include a computer program, program code,
instructions, or some combination thereof, for independently or
collectively instructing or configuring a hardware device to
operate as desired. The computer program and/or program code may
include program or computer-readable instructions, software
components, software modules, data files, data structures, and/or
the like, capable of being implemented by one or more hardware
devices, such as one or more of the hardware devices mentioned
above. Examples of program code include both machine code produced
by a compiler and higher level program code that is executed using
an interpreter.
[0065] For example, when a hardware device is a computer processing
device (e.g., a processor, Central Processing Unit (CPU), a
controller, an arithmetic logic unit (ALU), a digital signal
processor, a microcomputer, a microprocessor, etc.), the computer
processing device may be configured to carry out program code by
performing arithmetical, logical, and input/output operations,
according to the program code. Once the program code is loaded into
a computer processing device, the computer processing device may be
programmed to perform the program code, thereby transforming the
computer processing device into a special purpose computer
processing device. In a more specific example, when the program
code is loaded into a processor, the processor becomes programmed
to perform the program code and operations corresponding thereto,
thereby transforming the processor into a special purpose
processor.
[0066] Software and/or data may be embodied permanently or
temporarily in any type of machine, component, physical or virtual
equipment, or computer storage medium or device, capable of
providing instructions or data to, or being interpreted by, a
hardware device. The software also may be distributed over network
coupled computer systems so that the software is stored and
executed in a distributed fashion. In particular, for example,
software and data may be stored by one or more computer readable
recording mediums, including the tangible or non-transitory
computer-readable storage media discussed herein.
[0067] Even further, any of the disclosed methods may be embodied
in the form of a program or software. The program or software may
be stored on a non-transitory computer readable medium and is
adapted to perform any one of the aforementioned methods when run
on a computer device (a device including a processor). Thus, the
non-transitory, tangible computer readable medium, is adapted to
store information and is adapted to interact with a data processing
facility or computer device to execute the program of any of the
above mentioned embodiments and/or to perform the method of any of
the above mentioned embodiments.
[0068] Example embodiments may be described with reference to acts
and symbolic representations of operations (e.g., in the form of
flow charts, flow diagrams, data flow diagrams, structure diagrams,
block diagrams, etc.) that may be implemented in conjunction with
units and/or devices discussed in more detail below. Although
discussed in a particularly manner, a function or operation
specified in a specific block may be performed differently from the
flow specified in a flowchart, flow diagram, etc. For example,
functions or operations illustrated as being performed serially in
two consecutive blocks may actually be performed simultaneously, or
in some cases be performed in reverse order.
[0069] According to one or more example embodiments, computer
processing devices may be described as including various functional
units that perform various operations and/or functions to increase
the clarity of the description. However, computer processing
devices are not intended to be limited to these functional units.
For example, in one or more example embodiments, the various
operations and/or functions of the functional units may be
performed by other ones of the functional units. Further, the
computer processing devices may perform the operations and/or
functions of the various functional units without sub-dividing the
operations and/or functions of the computer processing units into
these various functional units.
[0070] Units and/or devices according to one or more example
embodiments may also include one or more storage devices. The one
or more storage devices may be tangible or non-transitory
computer-readable storage media, such as random access memory
(RAM), read only memory (ROM), a permanent mass storage device
(such as a disk drive), solid state (e.g., NAND flash) device,
and/or any other like data storage mechanism capable of storing and
recording data. The one or more storage devices may be configured
to store computer programs, program code, instructions, or some
combination thereof, for one or more operating systems and/or for
implementing the example embodiments described herein. The computer
programs, program code, instructions, or some combination thereof,
may also be loaded from a separate computer readable storage medium
into the one or more storage devices and/or one or more computer
processing devices using a drive mechanism. Such separate computer
readable storage medium may include a Universal Serial Bus (USB)
flash drive, a memory stick, a Blu-ray/DVD/CD-ROM drive, a memory
card, and/or other like computer readable storage media. The
computer programs, program code, instructions, or some combination
thereof, may be loaded into the one or more storage devices and/or
the one or more computer processing devices from a remote data
storage device via a network interface, rather than via a local
computer readable storage medium. Additionally, the computer
programs, program code, instructions, or some combination thereof,
may be loaded into the one or more storage devices and/or the one
or more processors from a remote computing system that is
configured to transfer and/or distribute the computer programs,
program code, instructions, or some combination thereof, over a
network. The remote computing system may transfer and/or distribute
the computer programs, program code, instructions, or some
combination thereof, via a wired interface, an air interface,
and/or any other like medium.
[0071] The one or more hardware devices, the one or more storage
devices, and/or the computer programs, program code, instructions,
or some combination thereof, may be specially designed and
constructed for the purposes of the example embodiments, or they
may be known devices that are altered and/or modified for the
purposes of example embodiments.
[0072] A hardware device, such as a computer processing device, may
run an operating system (OS) and one or more software applications
that run on the OS. The computer processing device also may access,
store, manipulate, process, and create data in response to
execution of the software. For simplicity, one or more example
embodiments may be exemplified as a computer processing device or
processor; however, one skilled in the art will appreciate that a
hardware device may include multiple processing elements or
processors and multiple types of processing elements or processors.
For example, a hardware device may include multiple processors or a
processor and a controller. In addition, other processing
configurations are possible, such as parallel processors.
[0073] The computer programs include processor-executable
instructions that are stored on at least one non-transitory
computer-readable medium (memory). The computer programs may also
include or rely on stored data. The computer programs may encompass
a basic input/output system (BIOS) that interacts with hardware of
the special purpose computer, device drivers that interact with
particular devices of the special purpose computer, one or more
operating systems, user applications, background services,
background applications, etc. As such, the one or more processors
may be configured to execute the processor executable
instructions.
[0074] The computer programs may include: (i) descriptive text to
be parsed, such as HTML (hypertext markup language) or XML
(extensible markup language), (ii) assembly code, (iii) object code
generated from source code by a compiler, (iv) source code for
execution by an interpreter, (v) source code for compilation and
execution by a just-in-time compiler, etc. As examples only, source
code may be written using syntax from languages including C, C++, C
#, Objective-C, Haskell, Go, SQL, R, Lisp, Java.RTM., Fortran,
Perl, Pascal, Curl, OCaml, Javascript.RTM., HTML5, Ada, ASP (active
server pages), PHP, Scala, Eiffel, Smalltalk, Erlang, Ruby,
Flash.RTM., Visual Basic.RTM., Lua, and Python.RTM..
[0075] Further, at least one embodiment of the invention relates to
the non-transitory computer-readable storage medium including
electronically readable control information (procesor executable
instructions) stored thereon, configured in such that when the
storage medium is used in a controller of a device, at least one
embodiment of the method may be carried out.
[0076] The computer readable medium or storage medium may be a
built-in medium installed inside a computer device main body or a
removable medium arranged so that it can be separated from the
computer device main body. The term computer-readable medium, as
used herein, does not encompass transitory electrical or
electromagnetic signals propagating through a medium (such as on a
carrier wave); the term computer-readable medium is therefore
considered tangible and non-transitory. Non-limiting examples of
the non-transitory computer-readable medium include, but are not
limited to, rewriteable non-volatile memory devices (including, for
example flash memory devices, erasable programmable read-only
memory devices, or a mask read-only memory devices); volatile
memory devices (including, for example static random access memory
devices or a dynamic random access memory devices); magnetic
storage media (including, for example an analog or digital magnetic
tape or a hard disk drive); and optical storage media (including,
for example a CD, a DVD, or a Blu-ray Disc). Examples of the media
with a built-in rewriteable non-volatile memory, include but are
not limited to memory cards; and media with a built-in ROM,
including but not limited to ROM cassettes; etc. Furthermore,
various information regarding stored images, for example, property
information, may be stored in any other form, or it may be provided
in other ways.
[0077] The term code, as used above, may include software,
firmware, and/or microcode, and may refer to programs, routines,
functions, classes, data structures, and/or objects. Shared
processor hardware encompasses a single microprocessor that
executes some or all code from multiple modules. Group processor
hardware encompasses a microprocessor that, in combination with
additional microprocessors, executes some or all code from one or
more modules. References to multiple microprocessors encompass
multiple microprocessors on discrete dies, multiple microprocessors
on a single die, multiple cores of a single microprocessor,
multiple threads of a single microprocessor, or a combination of
the above.
[0078] Shared memory hardware encompasses a single memory device
that stores some or all code from multiple modules. Group memory
hardware encompasses a memory device that, in combination with
other memory devices, stores some or all code from one or more
modules.
[0079] The term memory hardware is a subset of the term
computer-readable medium. The term computer-readable medium, as
used herein, does not encompass transitory electrical or
electromagnetic signals propagating through a medium (such as on a
carrier wave); the term computer-readable medium is therefore
considered tangible and non-transitory. Non-limiting examples of
the non-transitory computer-readable medium include, but are not
limited to, rewriteable non-volatile memory devices (including, for
example flash memory devices, erasable programmable read-only
memory devices, or a mask read-only memory devices); volatile
memory devices (including, for example static random access memory
devices or a dynamic random access memory devices); magnetic
storage media (including, for example an analog or digital magnetic
tape or a hard disk drive); and optical storage media (including,
for example a CD, a DVD, or a Blu-ray Disc). Examples of the media
with a built-in rewriteable non-volatile memory, include but are
not limited to memory cards; and media with a built-in ROM,
including but not limited to ROM cassettes; etc. Furthermore,
various information regarding stored images, for example, property
information, may be stored in any other form, or it may be provided
in other ways.
[0080] The apparatuses and methods described in this application
may be partially or fully implemented by a special purpose computer
created by configuring a general purpose computer to execute one or
more particular functions embodied in computer programs. The
functional blocks and flowchart elements described above serve as
software specifications, which can be translated into the computer
programs by the routine work of a skilled technician or
programmer.
[0081] Although described with reference to specific examples and
drawings, modifications, additions and substitutions of example
embodiments may be variously made according to the description by
those of ordinary skill in the art. For example, the described
techniques may be performed in an order different with that of the
methods described, and/or components such as the described system,
architecture, devices, circuit, and the like, may be connected or
combined to be different from the above-described methods, or
results may be appropriately achieved by other components or
equivalents.
[0082] At least one embodiment of the inventive method for image
noise reduction, in particular of x-ray images, comprises:
[0083] Production of a recorded image.
[0084] The recorded image is recorded in this case by a radiology
device or by a computed tomograph and inevitably contains noise. It
should be noted that the following steps can be applied to
reconstructed images or to raw data. Therefore a reconstructed
image and also raw data of an image can be understood as a recorded
image. Any given number of processing steps can also have been
applied however. Likewise further processing steps can be applied
after the method. For example the reconstruction of tomosynthesis
recordings or the creation of synthetic 2D images from the
tomosynthesis recordings. The method is preferably applied to raw
data, since in the data the statistical characteristics of the
noise are known or can be measured. Raw data can be detector
intensity values for example, for which detector-dependent
corrections can also have been applied, such as for example the
correction of defective pixels. Preferably however further
processing steps such as for example scattered radiation
correction, contrast adaptation, edge reinforcement have not yet
been applied during image recording. The recorded image can also
involve transformed raw data. For example it can be helpful to
apply an Anscombe transformation to the raw data. With this step
Poisson noise is converted into white noise (Gaussian noise with a
standard deviation of one). This allows the characteristics of the
noise to be better described. If CT data is used it should be noted
that the characteristics of the noise can depend additionally for
example on the reconstruction kernel used.
[0085] Establishing of an amount of noise of the recorded
image.
[0086] This amount of noise is established via methods for image
analysis. Suitable methods are known to the person skilled in the
art. Basically it is of no importance for the method which method
is applied, provided an amount of noise is established, wherein
naturally the quality of the result (the denoised image) depends on
the quality of the amount of noise established. The inventive
method serves in this case to improve a given noise reduction
method. Known (and preferred) image noise reduction algorithms are
the above-mentioned methods BM3D, IRIS (iterative CT image filters
for noise reduction) or methods that establish the amount of noise
with AI. The entire image in this case is divided into a noise
component and a component of image-relevant information, wherein
the latter does not absolutely have to be established but can serve
to improve the noise reduction algorithm.
[0087] Up to this point the method corresponds to the prior art, in
which the component of the image is considered that was recognized
by the algorithm as noise, and is then deducted from the original
image in order to obtain the noise-free or noise-reduced image. The
improvement as claimed in the invention is now produced by the
following steps.
[0088] Decomposition of the amount of noise into a defined number
of N frequency-dependent noise components for N frequency bands,
wherein the noise components comprise data points, which reflect
the noise in the recorded image for the frequency band
concerned.
[0089] A frequency-based decomposition of recorded images is well
known in the prior art. An example of this is a two-dimensional
Fourier decomposition, in particular a Fast-Fourier transformation,
or a wavelet transformation. Since the amount of noise corresponds
by its nature to a recorded image (either an image or raw data of
an image which represents the noise), a frequency-based
decomposition of the amount of noise is thus possible.
Unsharpnesses and sharpnesses, for which the information can be
found in frequency bands, belong to the characteristics of digital
images. In order to establish the individual frequency bands,
filter kernels or a Fourier transformation can be used for example.
The noise component can also be convoluted with a Gaussian filter
(or with another lowpass filter), wherein the difference between
the original and the filtered noise component represents the first
frequency band. Then, with the filtered noise component the further
process is exactly the same until the desired number of frequency
bands is reached. The "rest" of the noise is then preferably to be
found in the last frequency band. The number of frequency bands
into which the noise component is decomposed and how wide these are
(i.e. how wide the Gaussian filter is), should be set with the aid
of the system attributes. A decomposition takes place especially
preferably based on (such) a Laplace pyramid and will be explained
in greater detail below.
[0090] The data points correspond to the information of the
recording. In the case in which a reconstructed image is examined,
the data points preferably correspond to the image points (pixels)
of the image. In the case in which the recorded image comprises raw
data, the data points correspond to image-relevant information of
the raw data.
[0091] For a good decomposition knowledge of noise power spectrum
of the input image to be expected should exist. This is given in
particular for a plurality of medical imaging methods (e.g. CT,
tomosynthesis or digital x-ray) or can be determined by a
calibration if necessary. For example the characteristics of the
noise (electronic noise: Gauss-distributed, photon noise:
Poisson-distributed) are known for x-ray images and can either be
derived directly from the recording parameters, measured (noise
power spectrum) or calibrated. They can also be computed however
when enough knowledge about the imaging system is available. This
means that the statistical characteristics of the noise in the
individual frequency bands is known.
Examination of the noise components (for a number of their image
points/all image points) for (statistical) outlier image points of
which the intensity lies outside a predetermined range of values
and formation of moderate noise components by moderation of the
values of the outlier image points established in the
examination.
[0092] For example the statistics in the noise components (the
"noise frequency bands") can be described via the standard
deviation .sigma. and the average value. If a value in a noise
frequency band now lies more than 3.sigma. away from the average
value, the value is highly likely to be an outlier, if a Gauss-type
distribution is assumed. This threshold value can naturally also
assume another value, likewise other parameters can be used to
describe the noise statistics.
[0093] Subtraction of the moderated noise components from the
recorded image.
[0094] This step is similar to the prior art wherein, unlike in the
prior art, it is not the amount of noise that is taken away, but
the moderated amount of noise (or the moderated noise components).
The moderated noise components in this case can first be combined
into a moderated amount of noise. They can however also be directly
subtracted from the image individually. In practice a noise
intensity value established for each pixel can simply be subtracted
for each pixel from the intensity value (e.g. gray value) of the
pixels, wherein a negative noise intensity value is naturally added
in this context.
[0095] Thus the amount of noise is decomposed into a defined number
of N noise components, which are examined afterwards in each data
point or image point for statistical outliers, which are dealt with
in a dedicated way (moderated). After moderation of the noise
components the resulting moderated amount of noise is subtracted
from the original image. The method described is thus intended to
be applied to x-ray images after any given method for noise
reduction. In such cases, it prevents relevant image contents being
changed by the noise reduction method, by a bad choice of
parameters for example.
[0096] Thus noise in dedicated frequency bands is considered within
the framework of the invention.
[0097] An inventive apparatus for image noise reduction comprises
the following components:
[0098] An (in particular medical) imaging system designed to
produce a recorded image or a data interface for receiving a
recorded image, e.g. a radiography system, mammography system (also
tomosynthesis), fluoroscopy system or a computed tomography
system,
[0099] A noise reduction unit designed to establish an amount of
noise of the recorded image,
[0100] A decomposition unit designed to decompose the amount of
noise into a predetermined number of N frequency-band-dependent
noise components for N frequency bands, wherein the noise
components comprise data points, which reproduce the noise at
points in the recorded image for the frequency band concerned,
[0101] A moderation unit designed to examine the noise components
for outlier data points, the intensity of which lies outside a
predetermined range of values and for formation of moderated noise
components by moderation of the value of the outlier data points
established in the noise components in the examination,
[0102] Optionally a combination unit, which is designed to combine
the moderated noise components into a moderated amount of noise,
(before these are subtracted from the recorded image by the
subsequent subtraction unit), and
[0103] A subtraction unit designed to subtract the moderated noise
components from the recorded image.
[0104] An inventive control facility for control of an imaging
system, in particular a medical imaging system (in particular for
x-ray images), preferably a radiography system, fluoroscopy system,
mammography system or a computed tomography system, is designed for
carrying out an embodiment of an inventive method and/or comprises
an embodiment of an inventive apparatus.
[0105] An inventive imaging system, in particular a medical imaging
system, preferably a radiography system, fluoroscopy system,
mammography system or a computed tomography system, comprises an
embodiment of an inventive control facility.
[0106] A main focus of an embodiment of the invention is on x-ray
images of all kinds, in particular within the framework of computed
tomography (CT), cone beam CT, classical (digital) radiography and
fluoroscopy, mammography, tomosynthesis, and also on synthetic 2D
images computed therefrom (for mammography and other radiographic
applications such as for example lung imaging), DVT scanners for
dental and HNO applications, line scanners (e.g. EOS system), bone
density scanners (DXA) and other dual-energy x-ray images. These
recording methods and recording devices are preferred methods or
devices within the framework of the invention. In principle this
invention is however also able to be applied within the framework
of other imaging methods for which the noise characteristics are
known.
[0107] A large part of the components specified above of the
apparatus or of the control facility can be realized entirely or in
part in the form of software modules in a processor of a
corresponding apparatus or control facility. A largely
software-based realization has the advantage that even apparatuses
and control facilities previously used can be upgraded in a simple
manner by a software update in order to work in an inventive way.
To this extent the object is also achieved by a corresponding
computer program product with a computer program, which is able to
be loaded directly into a processing system or a memory facility of
a control facility (e.g. of a computed tomography system), with
program sections for carrying out all steps of the inventive method
when the program is executed in the processing system or the
control facility. Such a computer program product, as well as the
computer program, can if necessary comprise additional elements,
such as e.g. documentation and/or additional components including
hardware components, such as e.g. hardware keys (dongles etc.) for
using the software.
[0108] A computer-readable medium, e.g. a memory stick, a hard disk
or any other transportable or permanently-installed data medium, on
which the program sections of the computer program able to be read
in and executed by a processing system or a processing unit of the
control facility are stored can serve for transport to the
processing system or to the control facility and/or for storage at
or in the processing system or the control facility. For this
purpose the processing unit can have one or more microprocessors or
the like working together for example.
[0109] Further especially advantageous embodiments and developments
of the invention emerge from the dependent claims and also from the
description given below, wherein the claims of one claim category
can also be developed in a similar way to the claims and parts of
the description for another claim category and in particular
individual features of different example embodiments or variants
can be combined into new example embodiments or variants.
[0110] In accordance with a preferred method of an embodiment the
recorded image has been produced via x-rays, in particular within
the framework of a recording method of radiography, fluoroscopy,
mammography, tomography or computed tomography. The recorded image
is thus preferably an x-ray image or a CT image. Especially
preferably the recorded image is based on a mammography recording
and/or a tomosynthesis recording and is in particular a synthetic
2D image computed from a tomosynthesis recording or an image of an
intermediate step of such a computation.
[0111] In accordance with a preferred method of an embodiment the
amount of noise of the recorded image is established via a
conventional image noise reduction algorithm. A preferred
conventional image noise reduction algorithm is based on BM3D
and/or IRIS (see above) and/or on artificial intelligence. In this
method the recorded image is preferably subdivided into the amount
of noise and a component of conventional image information ("image
information", since this represents a denoised image,
"conventional", since this corresponds to the prior art and is only
optimized by the method). The conventional image information in
this case represents the denoised image in accordance with the
image noise reduction algorithm used and can be used together with
the denoised image in accordance with the invention to improve the
image noise reduction algorithm, e.g. for training an algorithm
capable of learning.
[0112] In accordance with a preferred method of an embodiment the
decomposition of the amount of noise is done based on a Laplacian
pyramid. A Gaussian or Laplacian pyramid, sometimes also called a
Burt-Adelson pyramid, is a digital signal processing algorithm and
is well known in the prior art for frequency-dependent
decomposition of images.
[0113] As an alternative the decomposition of the amount of noise
can also be done based on a Fast-Fourier transformation or a
wavelet transformation. These transformations are known to the
person skilled in the art.
[0114] In accordance with a preferred method of an embodiment, the
data points of the noise components are image points of an image or
they can be reconstructed to form image points of an image, which
represents the noise component concerned for the frequency band
concerned.
[0115] In accordance with a preferred method of an embodiment the
examination of the noise components for outlier data points and the
formation of moderated noise components is done by a moderation
function. This moderation function moderates the values of those
data points that lie outside a predetermined range of values and
preferably leaves the values of the data points within the range of
values unchanged. This moderation preferably takes place such that
values outside a value interval are changed so that they lie closer
to the average value of the value interval. It is preferred in this
case that the values of those data points that lie outside a
predetermined range of values are changed by the moderation
function so that they lie within the predetermined range of values,
preferably in which the values of the data points concerned are set
to the limits of the predetermined range of values or, with an
increasing distance from the predetermined range of values, are
adapted to be closer to the average value of the predetermined
range of values. For example values that lie above or below a
threshold value can be set to this threshold value (which would
represent the moderation) or be moderated so that, as their
distance from the threshold value increases, they are pulled back
ever closer towards the average value M.
[0116] In accordance with a preferred method of an embodiment a
combination of the moderated noise components with the outlier data
points dealt with to form a resulting amount of noise is done
before the subtraction of the moderated noise components from the
recorded image.
[0117] In general it can be the about the outliers that, in a
predetermined statistical distribution (e.g. Gauss or Poisson),
these represent statistical outliers and are changed so that they
"fit" the distribution again.
[0118] If Fn is a moderation function, An a noise component and Mn
a moderated noise component for the nth frequency band, then
preferably: Mn=Fn(An) applies.
[0119] It is generally preferred that the frequency bands of the
noise components taken together produce a contiguous frequency
range. Or the noise component in its entirety should be divided up
so that there are no non-allocated noise components that lie at
frequencies between two noise components used for the method.
Frequencies at which no noise components lie do not necessarily
have to be considered here.
[0120] In accordance with a preferred method of an embodiment, as a
part of recording the image, a noise behavior of equipment used for
recording is measured and/or calibrated. It is preferred in this
case that the moderation function depends on the measured noise
behavior and/or the image recording takes place after the
calibration. "Calibration" in this case means a noise-related
calibration, which takes account of or evaluates the nature of the
noise. For example the components of Gaussian noise or Poisson
noise, which are mathematically well known, are established via the
calibration. The more precisely the noise components are known, the
better the amount of noise in noise components is able to be
decomposed and moderation functions established with which outliers
can be moderated. The technique of calibration is known to the
person skilled in the art.
[0121] In accordance with a preferred method of an embodiment the
amount of noise is preferably decomposed into more than two noise
components, preferably into three noise components. Naturally it is
possible for more noise components to be used, however it has been
shown that, with a suitable choice of noise bands, not more than 3
are needed in order to achieve a good result. Preferably those
noise components with the highest frequency bands are chosen and
especially preferably a noise component comprises the "rest" of the
amount of noise, so that the amount of noise is contained fully in
the noise components.
[0122] Preferably components of the invention are present as a
"Cloud service". Such a Cloud service serves to process data, in
particular via an artificial intelligence, but can also be a
service based on conventional algorithms or a service in which an
evaluation by human beings takes place in the background. In
general a Cloud service (also referred to below as a "Cloud" for
short) is an IT infrastructure in which for example storage space
or processing power and/or application software is made available
via a network. Communication between the user and the Cloud takes
place in such cases via data interfaces and/or data transmission
protocols. In the present example it is especially preferred for
the Cloud service to make available both processing power and also
application software.
[0123] Within the framework of a preferred method of an embodiment
there is a provision of data via the network to the Cloud service.
This comprises a processing system, e.g. a computer cluster, which
as a rule does not include the user's local computer. This Cloud
can in particular be made available by the (medical) facility,
which also makes available the (medical) systems. For example the
data of an image recording is sent via an RIS (Radiology
Information System) or PACS to a (remote) processor system (the
Cloud). Preferably the processing system of the Cloud, the network
and also the (medical) system represent a cluster in the data
processing sense. The method can be realized in this case by a
command constellation in the network. The data computed in the
Cloud ("result data") is later sent back via the network to the
user's local computer.
[0124] The advantage of at least one embodiment of the invention is
that the application of a frequency-based method with specific
regard to AI-based methods delivers a high level of resulting
faithful images, since in particular the risk of structures being
removed, emphasized or added in by the noise reduction is curbed.
The method is especially advantageous for noise reduction
algorithms of which the performance is greatly determined by image
content that cannot be foreseen, i.e. AI-based methods for example,
although they have been trained and tested on sufficiently large
but finite datasets.
[0125] In the following explanations it is assumed that the imaging
equipment involves a computed tomography system. Basically however
the method is also able to be used in other imaging equipment
within medical engineering and outside of it.
[0126] FIG. 1 shows a rough schematic of a computed tomography
system 1 with a control facility 5 for carrying out an embodiment
of the inventive method. In the usual way the computed tomography
system 1 has a scanner 2 with a gantry, in which an x-ray source 3
rotates, which in each case irradiates a patient P who is pushed
into a measuring chamber of the gantry via a couch, so that the
radiation strikes a detector 4 lying opposite the x-ray source 3 in
each case. It is expressly pointed out that this example embodiment
only involves an example of a CT and the invention can also be used
on any given CT constructions, for example with annular fixed x-ray
detector and/or a number of x-ray sources.
[0127] Likewise in the control facility 5 only the components that
are of significance for the explanation of the invention are shown.
Basically these types of CT systems and associated control
facilities are known to the person skilled in the art and therefore
do not need to be explained in detail. A core component of the
control facility 5 here is a processor, on which different
components, here in particular an embodiment of the inventive
apparatus 6, are realized in the form of software modules. The
control facility 5 in this case has an interface, to which a
terminal 7 is connected, via which an operator can operate the
control facility 5 and thus can operate the computed tomography
system 1.
[0128] The apparatus 6 in the control facility 5 comprises a noise
reduction unit 8, a decomposition unit 9, a moderation unit 10, a
combination unit 11 and a subtraction unit 12, which will be
described below in greater detail together with the execution
sequence of the method.
[0129] FIG. 2 illustrates the nature of the frequency-dependent
noise components A1, A2, A3, A4, A5, A6, A7, A8. An amount of noise
RB (noise of the entire recorded image B, see e.g. FIG. 6) is
decomposed into 8 frequency-dependent noise components A1, A2, A3,
A4, A5, A6, A7, A8. For improved clarity the intensity is adapted
to the individual noise components A1, A2, A3, A4, A5, A6, A7, A8.
The main noise is contained in the first three noise components A1,
A2, A3.
[0130] FIG. 3 shows a flowchart for a possible execution sequence
of an embodiment of an inventive method. First of all a recorded
image B is produced. This recorded image B will be more or less
affected by noise and is to be denoised by way of an embodiment of
the inventive method.
[0131] To this end the amount of noise RB of the recorded image B
is first established in a noise reduction unit 8. This will
naturally not be the true noise component, but merely that
component which the (conventional) algorithm used for this purpose
for noise reduction estimates as the noise component. In addition
the conventional image information B1 (an image SdT denoised with
the algorithm, see FIG. 6) can be established, which is shown here
by a dashed outline. It should be noted that a denoising algorithm
as a rule delivers the conventional image information BI (i.e. a
conventional noise-reduced image) and the amount of noise RB is
produced in this case by a subtraction of the conventional image
information BI from the recorded image B.
[0132] The amount of noise RB established is then decomposed in the
decomposition unit 9 into a plurality of frequency-dependent noise
components A1, A2, An. The decomposition can be done here based
upon a Laplace pyramid for example. In this case the noise
components A1, A2, An comprise image points (or data points), which
reproduce noise at points of the recorded image for the frequency
band concerned.
[0133] These noise components A1, A2, An are now examined in a
moderation unit 10 for statistical outlier image points, the
intensities of which lie outside a predetermined range of values.
This can be done via a moderation function F, which can be used at
the same time for the formation of moderated noise components M1,
M2, Mn (see FIG. 4 or 5), by the moderation function F being used
to moderate the values of the outlier image points A1, A2, An in
the noise components established in the examination.
[0134] The modulation function F in this particular example is
chosen to be the same in each case. Typically however it will be
chosen individually (different) for each frequency band. The
threshold value which specifies the value from which moderation is
to take place can in this case also have a different value in each
frequency band.
[0135] In a subsequent combination unit 11 the moderated noise
components M1, M2, Mn are combined into a moderated amount of noise
MB. This step is optional, since the method can also work with the
individual moderated noise components M1, M2, Mn.
[0136] Lastly the moderated noise components M1, M2, Mn, in the
form of the moderated amount of noise MB, are subtracted by a
subtraction unit 12 from the recorded image B and thus the denoised
image EB created.
[0137] In a preferred moderation function F values with an
intensity within the threshold value (e.g. with a deviation of less
than three times the standard deviation) are left as they are.
Values that lie outside are outliers and are set to a pre-defined
threshold value. Two preferred graphs for moderation functions F1,
F2 are presented below.
[0138] FIG. 4 shows a preferred moderation function graph F1, which
has the example threshold value of 3, which corresponds to a
deviation by three times the standard deviation. The X axis in this
graph reflects the pixel value in the noise component A1, A2, An,
the Y axis the pixel value in the moderated noise component M1, M2,
Mn. If this function is applied to the image points of an amount of
noise A1, A2, An, all values of points with values either side of
three times the standard deviation (greater or less) are set to the
corresponding three times the standard deviation (3 or -3). In
order to avoid a kink in the function there can still be a small
area in which it continuously tapers.
[0139] FIG. 5 shows a further preferred moderation function graph
F2, which not only restricts the amplitude of outliers but
increasingly suppresses it as the deviation increases. Here too the
threshold value equals 3, as in FIG. 4.
[0140] FIG. 6 shows a comparison of a result (denoised image EB) of
an embodiment of the invention with an example of a denoised image
according to the prior art (for better visualization incorrect
behavior has been simulated here). On the right in the middle can
be seen a reference image, which shows a mammography image. This
image only comprises a very slight noise component.
[0141] This reference image Ref has now been provided with an
amount of noise RB, which is shown on the left at the bottom. The
resulting noisy image is now the original image here, i.e. the
noisy recorded image B, and is shown on the left in the middle.
[0142] This recorded image is now t. Once by way of a conventional
method for image noise reduction and once with an embodiment of the
inventive method. The denoised image in accordance with the prior
art (the conventional image information BI according to FIG. 3) is
shown on the right at the top and has a clearly visible shadow in
the top left corner, which could be incorrectly interpreted as a
structure. By contrast the denoised image EB on the right at the
bottom, in which the noise reduction was undertaken according to
the inventive method, corresponds more to the reference image
Ref.
[0143] In FIG. 7 noise components A1, A2, An of the amount of noise
RB of FIG. 6 are shown and it is explained how the incorrect shadow
in the conventional image information BI in the example shown in
FIG. 6 is removed in accordance with the inventive method. The
amount of noise (shown on the left at the top) from FIG. 6 is
decomposed into n noise components A1, A2, An, of which those of
the first two frequency bands and of the nth frequency band are
shown on the left. In the first two noise components A1, A2 there
are few outliers visible or none at all, however in the nth
frequency band the bright outlier area that causes the shadow in
the conventional image information in FIG. 6 is plainly visible. On
the right, as well as the noise components A1, A2, An, the
modulated noise components M1, M2, Mn are shown. Although the first
two modulated noise components M1, M2 still strongly resemble the
first two noise components A1, A2 (on account of the few outliers),
in the last modulated noise component Mn compared to the last noise
component An the bright outlier area has been modulated, e.g. via
the function from FIG. 4.
[0144] Shown at the top on the right is the resulting modulated
amount of noise MB, which is produced from the modulated noise
components M1, M2, Mn. If this modulated amount of noise MB is
used, the denoised image EB in FIG. 6 no longer exhibits the shadow
of the conventional image information BI.
[0145] In conclusion it is pointed out once again that the method
described above in detail and also the computed tomography system 1
shown merely involve example embodiments, which can be modified by
the person skilled in the art in a wide diversity of ways without
departing from the field of the invention. Furthermore the use of
the indefinite article "a" or "an" does not exclude the features
concerned also being able to be present multiple times. Likewise
the terms "unit" and "module" do not exclude the components
concerned consisting of a number of interacting subcomponents,
which where necessary can also be spatially distributed.
[0146] Although the invention has been illustrated and described in
detail by the preferred embodiments, the invention is not limited
by the disclosed examples and other variations can be derived
herefrom by the person skilled in the art without departing from
the scope of protection of the invention.
[0147] Even if not explicitly stated, individual example
embodiments, or individual sub-aspects or features of these example
embodiments, can be combined with, or substituted for, one other,
if this is practical and within the meaning of the invention,
without departing from the present invention. Without being stated
explicitly, advantages of the invention that are described with
reference to one example embodiment also apply to other example
embodiments, where transferable.
[0148] Of course, the embodiments of the method according to the
invention and the imaging apparatus according to the invention
described here should be understood as being example. Therefore,
individual embodiments may be expanded by features of other
embodiments. In particular, the sequence of the method steps of the
method according to the invention should be understood as being
example. The individual steps can also be performed in a different
order or overlap partially or completely in terms of time.
[0149] The patent claims of the application are formulation
proposals without prejudice for obtaining more extensive patent
protection. The applicant reserves the right to claim even further
combinations of features previously disclosed only in the
description and/or drawings.
[0150] References back that are used in dependent claims indicate
the further embodiment of the subject matter of the main claim by
way of the features of the respective dependent claim; they should
not be understood as dispensing with obtaining independent
protection of the subject matter for the combinations of features
in the referred-back dependent claims. Furthermore, with regard to
interpreting the claims, where a feature is concretized in more
specific detail in a subordinate claim, it should be assumed that
such a restriction is not present in the respective preceding
claims.
[0151] Since the subject matter of the dependent claims in relation
to the prior art on the priority date may form separate and
independent inventions, the applicant reserves the right to make
them the subject matter of independent claims or divisional
declarations. They may furthermore also contain independent
inventions which have a configuration that is independent of the
subject matters of the preceding dependent claims.
[0152] None of the elements recited in the claims are intended to
be a means-plus-function element within the meaning of 35 U.S.C.
.sctn. 112 (f) unless an element is expressly recited using the
phrase "means for" or, in the case of a method claim, using the
phrases "operation for" or "step for."
[0153] Example embodiments being thus described, it will be obvious
that the same may be varied in many ways. Such variations are not
to be regarded as a departure from the spirit and scope of the
present invention, and all such modifications as would be obvious
to one skilled in the art are intended to be included within the
scope of the following claims.
* * * * *